VIS 2128 - Portfolio

Mike Lidwin | Fall 2021

introduction

^{Fig.01_Overview of Cities Studied (Lidwin via the Buckminster Fuller Institute, 2021)}

^{Lucy Fellowes once said, “Every map is someone’s way of getting you to look at the world his or her way.” (Lucy Fellowes, Smithsonian curator, quoted in Henrikson 1994 and in Kitchin, Perkins, and Dodge 2009). This course is my first formal class on map-making, and I’ve enjoyed thinking about the lense I inevitably communicate when visualizing various urban phenomena. Throughout this semester, I used R Studio and ArcGIS to develop a small breathe of maps, considering how these visualizations begin to reveal (and exclude) information about the cities studied. Each week, I spent time looking at different cities across the world, so that I can get an idea of how data availability differs between major global cities.}

Why did we use these specific parameters during the calculation of the fingerprints?

^{The following portfolio demonstrates a variety of skills, including:}

       ^{- displaying multiple vector layers on the same map}
       ^{- calculating and displaying relationships among point and polygon layers based on distance}
       ^{- aggregating point data to a layer of polygons}
       ^{- calculating and displaying accessibility, based on travel time}
       ^{- converting between raster layers and vector layers}
       ^{- displaying raster data on a map}
       ^{- georeferencing a raster image}
       ^{- displaying data on an interactive map}

GREATER BOSTON, MA

Here are two maps of Chelsea. I might include some text here about this set of maps.

Interactive Map

This interactive map demonstrates the following skills:

Displaying data on an interactive map

^{Fig.02_Week 6 Assignment (Lidwin, 2021)}

Isochrones of Walkability

This map shows isochrones based on transit travel times to the nearest school. It demonstrates the following skills:

Displaying multiple vector layers on the same map
Calculating and displaying accessibility, based on travel time

^{Fig.03_Week 4 Assignment (Khinda, Lidwin, Montoya, 2021)}

Accessibility for Biking

This map shows accessibility based on a distance-decay function of the walking time to the nearest transit stop. It demonstrates the following skills:

Displaying multiple vector layers on the same map
Calculating and displaying accessibility, based on travel time
Displaying raster data on a map

^{Fig.04_Week 5 Assignment (Khinda, Lidwin, Montoya, 2021)}

VENICE, ITALY

Here are two maps of Chelsea. I might include some text here about this set of maps.

Flood Projections for Venice

This map demonstrates the following skills:

Georeferencing a raster image
Convert between raster and vector images (created vector outlines of rasterized data for flood areas)

^{Fig.05_Week 2 Assignment (Jamal, Lidwin, McGlinchey, Prasad, 2021)}

WASHINGTON, DC

Here are two maps of San Luis Obispo, California. I might include some text here as well. ^{Fig.06_Week 3 Assignment (Bonanno, Lidwin, Myros 2021)}

^{Fig.07_Week 3 Assignment (Bonanno, Lidwin, Myros 2021)}